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Agile Data Strategy and Lean Execution


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Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?

Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics

Published in: Data & Analytics
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Agile Data Strategy and Lean Execution

  1. 1. Agile Data Strategy and Lean Execution Mario Faria @mariofaria Aug 22nd 2014
  2. 2. Agile data strategy and lean execution August 22, 2014 Moderator: Mario Faria Chief Data Officer, CDO Inc. Antanina Kapchonava Project Director, Data Driven Business
  3. 3. Participants Vik Manchanda Chief Infor mation Officer Mario Faria Chief Data Officer Mike Jennings Senior Director Enterprise Data Architecture
  4. 4. mario.faria@cdo-­‐‑ @mariofaria h0p://www.cdo-­‐‑ • One of the first Chief Data Officers in the world leading teams focused in Analytics, Data Monetization, Data Quality, Data Governance, Operations and Business Architecture • Currently he is the head of CDO, Inc., advising companies on how to cross the “data & analytics chasm” • Worked as a CDO for ServiceSource and Boa Vista (Equifax) • Worked for IBM, Accenture and Microsoft, leading projects related to BI, DW, CRM, Supply Chain, Web Development and Management Consulting • His motto is : "If you do not treat people, technology and data as economic assets, they will become liabilities“ Mario Faria Chief Da ta Officer
  5. 5. Mario Faria 5
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  8. 8. Mario Faria 8 How to transform data assets into competitive insights, that will drive business decisions and actions, using people, processes and technologies ?
  9. 9. Mario Faria 9 On data and analytics • Many problems with streamlining a data strategy • Major concerns with data management • How you can overcome the issues • What we have learned from the data journey
  10. 10. The Manifesto for Agile Software Development Mario Faria 10 • Individuals and interactions over processes and tools • Working software over comprehensive documentation • Customer collaboration over contract negotiation • Responding to change over following a plan
  11. 11. Mario Faria 11 Source : Leading Strategic Initiatives (
  12. 12. Data, Information, Analytics, Business Intelligence and Performance Management Mario Faria 12
  13. 13. Mario Faria 13 The Data Value Chain
  14. 14. Mario Faria 14
  15. 15. Mario Faria 15 The Deming Model : Production Viewed as a System
  16. 16. Mario Faria 16 Toyota Production System
  17. 17. Implementing Data Management Best Practices based on the Lean Principles that came from the Toyota Manufacturing Process
  18. 18. The Chief Data / Analytics / Digital Officer roles Mario Faria 18 Chief Data Officer (focused on data management) Chief Analytics Officer (focused on decision Chief Digital Officer (focused on digital transformation) management initiatives) The ultimate leader who creates and executes digital, data and analytics strategies to drive business value Copyright: Mario Faria 2014
  19. 19. How did some organiza/ons change to a data driven culture ?
  20. 20. Mario Faria 20 Executive Support
  21. 21. How AIG and Walgreens implemented some of these changes
  22. 22. Michael Jennings : Bio
  23. 23. Enterprise Data Strategy Brief 22 August 2014 Mike Jennings ©2014 Walgreen Co. All rights reserved. Confidential and proprietary information. All rights reserved.
  24. 24. Walgreens Company Overview
  25. 25. Data Opportunities Challenges to Fully Leveraging Data
  26. 26. Defining Enterprise Data Strategy
  27. 27. Why do we need this strategy? Enterprise Data Strategy will help:
  28. 28. Data Strategy Depends on Enterprise Data Management
  29. 29. Data Strategy Depends on Data Governance & Stewardship
  30. 30. Data Strategy Depends on Master Data & Reference Data
  31. 31. Data Strategy Depends on Data Quality
  32. 32. Data Strategy Depends on Enterprise Data Models & Data Integration
  33. 33. Data Strategy Depends on Leveraging Industry & National Standards
  34. 34. SAVE THE DATE! CDO EXECUTIVE FORUM 2014 NOVEMBER 12, 2014 - NEW YORK, NEW YORKER HOTEL CUTTING-EDGE RECOMMENDATIONS ON HOW TO: • Mobilize your C-suite and prepare your organization for a new data-driven culture • Translate your enterprise data assets into intelligence by reconsidering your approach to information management processes • Reach the consensus between the IT and business units to attain organizational efficiency and eliminate the dangers of siloed data • Get a granular view of your data: use analytics to separate clutter from meaningful information and boost your company’s profitability • Deliver highly actionable data through enhanced data management and analytics initiatives Find out more at: Call 201-204-1674 or email Register today with discount code WEBINAR0819 and save additional $100
  35. 35. Vik Manchanda Chief Information Officer RUTGERS UNIVERSITY, NJ B.A. – Computer Science COLUMBIA UNIVERSITY, NY CTA Diploma UCLA, CA Executive IT & Business Integration Coaching AIG Life and A&H Houston, 2012 – Present Senior Vice President, Chief Information Officer AIG Advisor Group Houston, 2009 – 2010 Sr. Consultant ACE Group, LTD. Houston, 2008 – 2009 Executive Vice President, Chief Architect & Data Officer AIG Global Services New York, 2005 – 2008 Vice President, Chief Strategy & Administration Officer AAIG Retirement Services Los Angeles, 2001 – 2005 Vice President, Senior Information Officer AIG Domestic Brokerage Group New York & INDIA, 1996 – 2001 Assistant Vice President, Information Services Group Bear Stearns, Inc.; New York, 1989 – 1996 Lehman Brothers; Citi Group; Suburban Propane; AT&T Affiliations: • SIPA • TiE • No Kid Goes Hungry • American Cancer Society
  36. 36. • Get Facts @ the right 36 time and the right place." • Use Facts everytime making crucial business decisions." • Preserve Facts." Winning with Data!
  37. 37. Big Data Practice 37 Our approach reverse that ratio offering maximum business value in Revenue generation, Operational efficiency and Compliance Business Intelligence Data Mining OAP Benchmarking BPR Data Warehousing Analytics Reporting Traditionally 75% of effort spent in data aggregation and transformation yields 25% in benefits Big Data
  38. 38. Three Good Winning Examples: ü At AIG, we use data gathered from physical exam and blood results and pass 38 them through a model jointly created along with John Hopkins University to predict mortality rates and based upon that we underwrite insured, resulting in significant reduction in claims & increase in net profits. ü At Ace, we created a model to apply to the insured to predict their risk level and accordingly either underwrote them with appropriate rate class or denied coverage. Same model was used to detect fraudulent claims. ü At AIG, we are using a combination of mobile and data strategy to converge distribution channels such that each agent is able to offer multiple lines of businesses to the customers, as opposed to traditionally just creating leads for the other lines of business. Further we are creating incentives for cross-selling and upselling that are visibly working.
  39. 39. Incent The Right Behavior • Link Compensation to Targets" • Create Commission 39 Transparency" • Allow Margin Control at Point of Sale" • Stricter Compliance and Governance" • Yield Higher Revenues" "
  40. 40. Debate
  41. 41. Participants Vik Manchanda Chief Infor mation Officer Mario Faria Chief Data Officer Mike Jennings Senior Director Enterprise Data Architecture
  42. 42. Q&A
  43. 43. Participants Vik Manchanda Chief Infor mation Officer Mario Faria Chief Data Officer Mike Jennings Senior Director Enterprise Data Architecture
  44. 44. Conclusions
  45. 45. Agile Data Strategy and Lean Execution Mario Faria @mariofaria